title: Swimming in light: a large-scale computational analysis of the metabolism of Dinoroseobacter shibae.
abstract: The Roseobacter clade is a ubiquitous group of marine α-proteobacteria. To gain insight into the versatile metabolism of this clade, we took a constraint-based approach and created a genome-scale metabolic model (iDsh827) of Dinoroseobacter shibae DFL12T. Our model is the first accounting for the energy demand of motility, the light-driven ATP generation and experimentally determined specific biomass composition. To cover a large variety of environmental conditions, as well as plasmid and single gene knock-out mutants, we simulated 391,560 different physiological states using flux balance analysis. We analyzed our results with regard to energy metabolism, validated them experimentally, and revealed a pronounced metabolic response to the availability of light. Furthermore, we introduced the energy demand of motility as an important parameter in genome-scale metabolic models. The results of our simulations also gave insight into the changing usage of the two degradation routes for dimethylsulfoniopropionate, an abundant compound in the ocean. A side product of dimethylsulfoniopropionate degradation is dimethyl sulfide, which seeds cloud formation and thus enhances the reflection of sunlight. By our exhaustive simulations, we were able to identify single-gene knock-out mutants, which show an increased production of dimethyl sulfide. In addition to the single-gene knock-out simulations we studied the effect of plasmid loss on the metabolism. Moreover, we explored the possible use of a functioning phosphofructokinase for D. shibae.
authors.affiliation: Department of Bioinformatics and Biochemistry, Technische Universität Braunschweig, Braunschweig, Germany.
authors.forename: Rene
authors.initials: R
authors.lastname: Rex
authors.forename: Nelli
authors.initials: N
authors.lastname: Bill
authors.forename: Kerstin
authors.initials: K
authors.lastname: Schmidt-Hohagen
authors.forename: Dietmar
authors.initials: D
authors.lastname: Schomburg
mesh_terms: D018533:Biomass; D019295:Computational Biology / Q000379:methods*; D064688:Metabolic Flux Analysis; D053858:Metabolic Networks and Pathways / Q000235:genetics* / Q000502:physiology*; D041902:Rhodobacteraceae / Q000235:genetics* / Q000378:metabolism* / Q000502:physiology